{
  "nbformat": 4,
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  "metadata": {
    "colab": {
      "name": "Chapter_07",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jo-cho/advances_in_financial_machine_learning/blob/master/Chapter_07.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WoyFdkpjxkxL",
        "colab_type": "text"
      },
      "source": [
        "## Why CV fails in finance ? \n",
        "\n",
        "One reason k-fold CV fails in finance is because observations\n",
        "cannot be assumed to be drawn from an IID process. A second reason for CV’s failure\n",
        "is that the testing set is used multiple times in the process of developing a model,\n",
        "leading to multiple testing and selection bias."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_lcNOTU_x8AZ",
        "colab_type": "text"
      },
      "source": [
        "## Solution is \n",
        "\n",
        "\n",
        "1. Purging the trains set\n",
        "2. Embargo\n",
        "3. The purged k-fold class\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zi_Ku62VufU_",
        "colab_type": "text"
      },
      "source": [
        "#1.\n",
        "Why is shuffling a dataset before conducting k-fold CV generally a bad idea in\n",
        "finance? What is the purpose of shuffling? Why does shuffling defeat the purpose\n",
        "of k-fold CV in financial datasets?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lcrX7GpQwcxT",
        "colab_type": "text"
      },
      "source": [
        "The general procedure of k-fold cv:\n",
        "\n",
        "1. Shuffle the dataset randomly.\n",
        "2. Split the dataset into k groups\n",
        "3. For each unique group:\n",
        "    1. Take the group as a hold out or test data set\n",
        "    2. Take the remaining groups as a training data set\n",
        "    3. Fit a model on the training set and evaluate it on the test set\n",
        "    4. Retain the evaluation score and discard the model\n",
        "4. Summarize the skill of the model using the sample of model evaluation scores"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4eazSpYe0LyT",
        "colab_type": "text"
      },
      "source": [
        ",but in finance ..."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a0awVhCr1Sxo",
        "colab_type": "text"
      },
      "source": [
        "# 2.\n",
        "Take a pair of matrices (X, y), representing observed features and labels. These\n",
        "could be one of the datasets derived from the exercises in Chapter 3."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_kWZQl2A4F8P",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G1EKrR492p-I",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "f45f93c3-6632-49b7-d659-3bf484d64c34"
      },
      "source": [
        "!pip install -q mlfinlab\n",
        "from mlfinlab import data_structures, features, filters, labeling, util, sampling"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[?25l\r\u001b[K     |██▊                             | 10kB 39.4MB/s eta 0:00:01\r\u001b[K     |█████▌                          | 20kB 6.2MB/s eta 0:00:01\r\u001b[K     |████████▎                       | 30kB 8.9MB/s eta 0:00:01\r\u001b[K     |███████████                     | 40kB 5.8MB/s eta 0:00:01\r\u001b[K     |█████████████▉                  | 51kB 7.0MB/s eta 0:00:01\r\u001b[K     |████████████████▋               | 61kB 8.3MB/s eta 0:00:01\r\u001b[K     |███████████████████▍            | 71kB 9.6MB/s eta 0:00:01\r\u001b[K     |██████████████████████▏         | 81kB 10.7MB/s eta 0:00:01\r\u001b[K     |█████████████████████████       | 92kB 11.9MB/s eta 0:00:01\r\u001b[K     |███████████████████████████▊    | 102kB 9.4MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▌ | 112kB 9.4MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 122kB 9.4MB/s \n",
            "\u001b[?25h"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HbbB4KO33iBM",
        "colab_type": "code",
        "outputId": "05e2a70a-15c9-45ae-e31d-00c1749ba9e5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DVZHX6TF2DEO",
        "colab_type": "code",
        "outputId": "32c5d5f9-177d-40c7-f055-aa564fd9f2e9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        }
      },
      "source": [
        "raw_dollar_bars = data_structures.get_dollar_bars('/content/drive/My Drive/Colab Notebooks/csv/clean_IVE_tickbidask2.csv', threshold=1000000)\n",
        "dollar_bars = raw_dollar_bars.set_index(pd.to_datetime(raw_dollar_bars.date_time))\n",
        "dollar_bars = dollar_bars.drop(columns='date_time')\n",
        "dollar_bars = dollar_bars.reset_index().drop_duplicates(subset='date_time', keep='last').set_index('date_time')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading data in batches:\n",
            "Batch number: 0\n",
            "Returning bars \n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3yLWUOVTGhZE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "close = dollar_bars.close\n",
        "pt_sl = [1,1]\n",
        "target = util.get_daily_vol(close)\n",
        "h = target.mean()\n",
        "t_events = filters.cusum_filter(close,h)\n",
        "vertical_barrier_times = labeling.add_vertical_barrier(t_events,close,num_days=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mdTJYd0HGwLt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# side (Chapter3)\n",
        "\n",
        "fast_window = 20\n",
        "slow_window = 50\n",
        "\n",
        "df = pd.DataFrame()\n",
        "df['fast_mavg'] = close.rolling(window=fast_window, min_periods=fast_window, center=False).mean()\n",
        "df['slow_mavg'] = close.rolling(window=slow_window, min_periods=slow_window, center=False).mean()\n",
        "df['side'] = np.nan\n",
        "\n",
        "long_signals = df['fast_mavg'] >= df['slow_mavg'] \n",
        "short_signals = df['fast_mavg'] < df['slow_mavg'] \n",
        "df.loc[long_signals, 'side'] = 1\n",
        "df.loc[short_signals, 'side'] = -1\n",
        "\n",
        "df['side'] = df['side'].shift(1)\n",
        "\n",
        "side = df['side']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4ccd7knnGwzK",
        "colab_type": "code",
        "outputId": "b0d8f199-1799-4e13-e988-083c22ae9956",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        }
      },
      "source": [
        "events = labeling.get_events(close, t_events, pt_sl, target, min_ret=0.005, num_threads=1, vertical_barrier_times = vertical_barrier_times ,side_prediction = side)\n",
        "bin = labeling.get_bins(events,close)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/mlfinlab/labeling/labeling.py:124: FutureWarning: \n",
            "Passing list-likes to .loc or [] with any missing label will raise\n",
            "KeyError in the future, you can use .reindex() as an alternative.\n",
            "\n",
            "See the documentation here:\n",
            "https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike\n",
            "  target = target.loc[t_events]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5EA7vjaeGzXQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "raw_data = pd.DataFrame()\n",
        "\n",
        "# Log Returns\n",
        "raw_data['log_ret'] = np.log(close).diff()\n",
        "\n",
        "# Momentum\n",
        "raw_data['mom1'] = close.pct_change(periods=1)\n",
        "raw_data['mom2'] = close.pct_change(periods=2)\n",
        "raw_data['mom3'] = close.pct_change(periods=3)\n",
        "raw_data['mom4'] = close.pct_change(periods=4)\n",
        "raw_data['mom5'] = close.pct_change(periods=5)\n",
        "\n",
        "# Volatility\n",
        "raw_data['volatility_50'] = raw_data['log_ret'].rolling(window=50, min_periods=50, center=False).std()\n",
        "raw_data['volatility_31'] = raw_data['log_ret'].rolling(window=31, min_periods=31, center=False).std()\n",
        "raw_data['volatility_15'] = raw_data['log_ret'].rolling(window=15, min_periods=15, center=False).std()\n",
        "\n",
        "# Serial Correlation (Takes about 4 minutes)\n",
        "window_autocorr = 50\n",
        "\n",
        "raw_data['autocorr_1'] = raw_data['log_ret'].rolling(window=window_autocorr, min_periods=window_autocorr, center=False).apply(lambda x: x.autocorr(lag=1), raw=False)\n",
        "raw_data['autocorr_2'] = raw_data['log_ret'].rolling(window=window_autocorr, min_periods=window_autocorr, center=False).apply(lambda x: x.autocorr(lag=2), raw=False)\n",
        "raw_data['autocorr_3'] = raw_data['log_ret'].rolling(window=window_autocorr, min_periods=window_autocorr, center=False).apply(lambda x: x.autocorr(lag=3), raw=False)\n",
        "raw_data['autocorr_4'] = raw_data['log_ret'].rolling(window=window_autocorr, min_periods=window_autocorr, center=False).apply(lambda x: x.autocorr(lag=4), raw=False)\n",
        "raw_data['autocorr_5'] = raw_data['log_ret'].rolling(window=window_autocorr, min_periods=window_autocorr, center=False).apply(lambda x: x.autocorr(lag=5), raw=False)\n",
        "\n",
        "# Get the various log -t returns\n",
        "raw_data['log_t1'] = raw_data['log_ret'].shift(1)\n",
        "raw_data['log_t2'] = raw_data['log_ret'].shift(2)\n",
        "raw_data['log_t3'] = raw_data['log_ret'].shift(3)\n",
        "raw_data['log_t4'] = raw_data['log_ret'].shift(4)\n",
        "raw_data['log_t5'] = raw_data['log_ret'].shift(5)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6Zw2iE9wG2yC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "outputId": "b409f140-292a-47f1-cded-8cde9cee9a91"
      },
      "source": [
        "raw_data2 = raw_data.shift(1)\n",
        "raw_data2['side'] = side\n",
        "raw_data3 = raw_data2.dropna()\n",
        "y=bin.bin\n",
        "X = raw_data3.loc[y.index,:]\n",
        "data = X.join(y,how='right').dropna()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/pandas/core/indexing.py:1418: FutureWarning: \n",
            "Passing list-likes to .loc or [] with any missing label will raise\n",
            "KeyError in the future, you can use .reindex() as an alternative.\n",
            "\n",
            "See the documentation here:\n",
            "https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike\n",
            "  return self._getitem_tuple(key)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HZRO6oJcHCrV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = data.iloc[:,:-1]\n",
        "y = data.iloc[:,-1]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pJkt2ZJw1fUk",
        "colab_type": "text"
      },
      "source": [
        "## (a) Derive the performance from a 10-fold CV of an RF classifier on (X, y), without shuffling."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QKL0Q7Xc1ZSh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import StratifiedKFold\n",
        "from sklearn.ensemble import RandomForestClassifier, BaggingClassifier\n",
        "from sklearn.metrics import roc_curve, confusion_matrix, auc"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q4cReR6pI5c7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Chapter 4\n",
        "un = sampling.get_av_uniqueness_from_triple_barrier(events, close,1)\n",
        "avgU = un.mean()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jRvrcFl3IZ7J",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Chapter 6\n",
        "clf = RandomForestClassifier(n_estimators=1,criterion='entropy',bootstrap=False,class_weight='balanced_subsample')\n",
        "clf = BaggingClassifier(base_estimator=clf,n_estimators=1000,max_samples=avgU,max_features=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VGHL2fQO5oMB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#clf0=RandomForestClassifier(n_estimators=1000,class_weight='balanced_subsample', criterion='entropy')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F2VEsdpTKISV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "skf = StratifiedKFold(n_splits=10, shuffle=False)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6T0aparbKYDp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from scipy import interp\n",
        "def crossValPlot(skf,classifier,X_,y_):\n",
        "    \"\"\"Code adapted from:\n",
        "        \n",
        "    \"\"\"\n",
        "    \n",
        "    X = np.asarray(X_)\n",
        "    y = np.asarray(y_)\n",
        "    \n",
        "    tprs = []\n",
        "    aucs = []\n",
        "    mean_fpr = np.linspace(0, 1, 100)\n",
        "    \n",
        "    f,ax = plt.subplots(figsize=(10,7))\n",
        "    i = 0\n",
        "    for train, test in skf.split(X, y):\n",
        "        probas_ = classifier.fit(X[train], y[train]).predict_proba(X[test])\n",
        "        # Compute ROC curve and area the curve\n",
        "        fpr, tpr, thresholds = roc_curve(y[test], probas_[:, 1])\n",
        "        tprs.append(interp(mean_fpr, fpr, tpr))\n",
        "        tprs[-1][0] = 0.0\n",
        "        roc_auc = auc(fpr, tpr)\n",
        "        aucs.append(roc_auc)\n",
        "        ax.plot(fpr, tpr, lw=1, alpha=0.3,\n",
        "                 label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n",
        "\n",
        "        i += 1\n",
        "\n",
        "    ax.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n",
        "             label='Luck', alpha=.8)\n",
        "\n",
        "    mean_tpr = np.mean(tprs, axis=0)\n",
        "    mean_tpr[-1] = 1.0\n",
        "    mean_auc = auc(mean_fpr, mean_tpr)\n",
        "    std_auc = np.std(aucs)\n",
        "    ax.plot(mean_fpr, mean_tpr, color='b',\n",
        "             label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n",
        "             lw=2, alpha=.8)\n",
        "\n",
        "    std_tpr = np.std(tprs, axis=0)\n",
        "    tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n",
        "    tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n",
        "    ax.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n",
        "                     label=r'$\\pm$ 1 std. dev.')\n",
        "\n",
        "    ax.set_xlim([-0.05, 1.05])\n",
        "    ax.set_ylim([-0.05, 1.05])\n",
        "    ax.set_xlabel('False Positive Rate')\n",
        "    ax.set_ylabel('True Positive Rate')\n",
        "    ax.set_title('Receiver operating characteristic example')\n",
        "    ax.legend(bbox_to_anchor=(1,1))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZZlB1XlGKdix",
        "colab_type": "code",
        "outputId": "d0f6420d-8b0c-4a88-f9fd-bdfb6f60a2fb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        }
      },
      "source": [
        "crossValPlot(skf,clf,X,y)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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XCw6HA7Gxsc1TDbtOn0bvPn1ooHwHMjMzG48fP64EgI0bNwZnZGSYs7KyGgBA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\ntIULF0YIwsUJsvLy8nqkpaUlJyQkpCY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tp+nK4/FAEAR0rPBNUZfS0qVL+1Sw8UoxatQo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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s8xnuaHe-OFd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "0cc49477-640b-425f-86ed-00f02cee5f49"
      },
      "source": [
        "cross_validation.ml_cross_val_score(clf,X,y=y,cv_gen=skf).mean()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.585958997770845"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hHWnVeAQMGuT",
        "colab_type": "text"
      },
      "source": [
        "## (b) Derive the performance from a 10-fold CV of an RF classifier on (X, y), with shuffling."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bfCKAiABLrmV",
        "colab_type": "code",
        "outputId": "c7402a64-fa10-4685-8237-9ea082f52c88",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        }
      },
      "source": [
        "skfb = StratifiedKFold(n_splits=10, shuffle=True)\n",
        "\n",
        "crossValPlot(skfb,clf,X,y)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UFBTkGQwG+ciRIxMfeOCBo21Nlfz3v//97NSpU02++3r06OH48ccfC8LDw4Xc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\nH3cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eMu0Ppc2-3_g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "f817b66f-042a-441f-e5fe-a9fb031cb613"
      },
      "source": [
        "cross_validation.ml_cross_val_score(clf,X,y=y,cv_gen=skfb).mean()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.579455479512213"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2bIMGf4Y4A7y",
        "colab_type": "text"
      },
      "source": [
        "둘다 전혀 좋은 결과는 아니지만 셔플한 샘플의 결과가 조금 더 괜찮다.\n",
        "하지만 overfit의 문제를 생각해봐야한다."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XB9Ijvvx6s8f",
        "colab_type": "text"
      },
      "source": [
        "## 3. Take the same pair of matrices (X, y) you used in exercise 2.\n",
        "\n",
        "(a) Derive the performance from a 10-fold purged CV of an RF on (X, y), with 1% embargo.\n",
        "\n",
        "(b) Why is the performance lower?\n",
        "\n",
        "(c) Why is this result more realistic?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t0igMmoYNVxL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from mlfinlab import cross_validation"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3nSWNR8f86EV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tmp_data = data.join(events['t1'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z8lNcXIr7JA2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pkf = cross_validation.PurgedKFold(n_splits=10, samples_info_sets=tmp_data['t1'], pct_embargo=0.01)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1xv2cFuI8Y37",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def crossValPlot2(skf,classifier,X,y):\n",
        "    \"\"\"Code adapted from:\n",
        "        \n",
        "    \"\"\"\n",
        "    from itertools import cycle\n",
        "    from sklearn.metrics import roc_curve, auc\n",
        "    from scipy import interp\n",
        "    \n",
        "    tprs = []\n",
        "    aucs = []\n",
        "    mean_fpr = np.linspace(0, 1, 100)\n",
        "    idx = pd.IndexSlice\n",
        "    f,ax = plt.subplots(figsize=(10,7))\n",
        "    i = 0\n",
        "    for train, test in skf.split(X, y):\n",
        "        probas_ = (classifier.fit(X.iloc[idx[train]], y.iloc[idx[train]])\n",
        "                   .predict_proba(X.iloc[idx[test]]))\n",
        "        # Compute ROC curve and area the curve\n",
        "        fpr, tpr, thresholds = roc_curve(y.iloc[idx[test]], probas_[:, 1])\n",
        "        tprs.append(interp(mean_fpr, fpr, tpr))\n",
        "        tprs[-1][0] = 0.0\n",
        "        roc_auc = auc(fpr, tpr)\n",
        "        aucs.append(roc_auc)\n",
        "        ax.plot(fpr, tpr, lw=1, alpha=0.3,\n",
        "                 label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc))\n",
        "\n",
        "        i += 1\n",
        "\n",
        "    ax.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r',\n",
        "             label='Luck', alpha=.8)\n",
        "\n",
        "    mean_tpr = np.mean(tprs, axis=0)\n",
        "    mean_tpr[-1] = 1.0\n",
        "    mean_auc = auc(mean_fpr, mean_tpr)\n",
        "    std_auc = np.std(aucs)\n",
        "    ax.plot(mean_fpr, mean_tpr, color='b',\n",
        "             label=r'Mean ROC (AUC = %0.2f $\\pm$ %0.2f)' % (mean_auc, std_auc),\n",
        "             lw=2, alpha=.8)\n",
        "\n",
        "    std_tpr = np.std(tprs, axis=0)\n",
        "    tprs_upper = np.minimum(mean_tpr + std_tpr, 1)\n",
        "    tprs_lower = np.maximum(mean_tpr - std_tpr, 0)\n",
        "    ax.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2,\n",
        "                     label=r'$\\pm$ 1 std. dev.')\n",
        "\n",
        "    ax.set_xlim([-0.05, 1.05])\n",
        "    ax.set_ylim([-0.05, 1.05])\n",
        "    ax.set_xlabel('False Positive Rate')\n",
        "    ax.set_ylabel('True Positive Rate')\n",
        "    ax.set_title('Receiver operating characteristic example')\n",
        "    ax.legend(bbox_to_anchor=(1,1))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HNkcJqtW8plC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "da6aa798-f07a-42dd-fcc2-9801f631f771"
      },
      "source": [
        "crossValPlot2(pkf,clf,X,y)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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0h0AGAF5//fXghx56qEEiOT+R7ebNmwOTkpJMmzZt8u9pfo899pgmICDAWVxcnJefn388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ZHnkKjgoW1hEERx6BBMU6dC++mnkAmBllLEx8ejQ4cOpxSgMAxzbmVlZbmKi4tVAPD222+H9urV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\nIiIiC4pCioiIiIiILCj/HxkfVpHQfibzAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "814CM_jV-7wn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "83fff56f-0bb8-426c-a8db-a0eedfe19624"
      },
      "source": [
        "cross_validation.ml_cross_val_score(clf,X,y=y,cv_gen=pkf).mean()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.5848593089259808"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VPiH1UwuAQoy",
        "colab_type": "text"
      },
      "source": [
        "결과는 사실 비슷함"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FLE1U4gK_xj5",
        "colab_type": "text"
      },
      "source": [
        "The performance is lowered because redundant samples are minimized, shuffling is removed thereby removing leakage and an additional layer of protection is implemented between the test sets and the following train sets. This is called an embargo which serves to further eliminate leakage between train and test sets."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mAA9BqGG8v98",
        "colab_type": "text"
      },
      "source": [
        "Preventing information leakage results in performance that is closer to out of sample performance where the future is unknowable."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I4SKrGuP_1qN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PF8vmACVBkb6",
        "colab_type": "text"
      },
      "source": [
        "참고 : github/BlackArbsCEO"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iFoWFzmmBqFn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}